Salient Region Detection Based on SLIC and Graph-based Segmentation

DOI

10.2991/amitp-16.2016.96How to use a DOI?

Keywords

saliency map; graph-based image segmentation; SLIC, color sparse histogram.

Abstract

At present, the most recent saliency detection algorithms are still not satisfactory. A saliency detection algorithm based on SLIC and graph-based segmentation is proposed. Firstly, graph-based segmentation is used to obtain larger image partitions, and the partitions with good contours are acquired. Then the relatively detailed partitions are obtained using SLIC image segmentation. Sparse color histogram is applied to these two methods. By using the color and spatial distance information, the saliency of each partition is calculated. Contours of salient objects from saliency maps generated using Graph-Based Segmentation are acquired and the gray scale values of the two kinds of saliency maps in the area surrounded by contours are merged. Experimental results show that compared with other detection methods, the proposed algorithm can effectively detect the salient object in the image.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaofei Sun
AU  - Wenwen Pan
AU  - Xia Wang
AU  - Xuhong Li
AU  - Guan Wang
PY  - 2016/09
DA  - 2016/09
TI  - Salient Region Detection Based on SLIC and Graph-based Segmentation
BT  - Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)
PB  - Atlantis Press
SP  - 482
EP  - 486
SN  - 2352-538X
UR  - https://doi.org/10.2991/amitp-16.2016.96
DO  - 10.2991/amitp-16.2016.96
ID  - Sun2016/09
ER  -